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README.md
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---
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base_model: finiteautomata/beto-sentiment-analysis
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tags:
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- generated_from_trainer
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model-index:
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- name: Analisis-sentimientos-BETO-TASS-C
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Analisis-sentimientos-BETO-TASS-C
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This model is a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.2393
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- Rmse: 0.7242
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rmse |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.8967 | 1.0 | 961 | 0.9813 | 0.6986 |
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| 0.7239 | 2.0 | 1922 | 1.0296 | 0.7517 |
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| 0.5218 | 3.0 | 2883 | 1.7505 | 0.7668 |
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| 0.3103 | 4.0 | 3844 | 2.0306 | 0.7242 |
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| 0.1974 | 5.0 | 4805 | 2.5881 | 0.7475 |
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| 0.0896 | 6.0 | 5766 | 2.7333 | 0.7551 |
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| 0.0444 | 7.0 | 6727 | 3.0139 | 0.7531 |
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| 0.0255 | 8.0 | 7688 | 3.1289 | 0.7177 |
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| 0.0137 | 9.0 | 8649 | 3.2251 | 0.7242 |
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| 0.0069 | 10.0 | 9610 | 3.2393 | 0.7242 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.18.0
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- Tokenizers 0.13.3
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